Oral cancer is one of the most common cancers. In the US there are over 39,000 new cases of oral cancer each year. It causes approximately 8,000 deaths per year, killing roughly 1 person per hour. One of the major clinical problems of oral cancer is the late detection of the disease. Improvement in patient survival requires a better understanding of oral cancer initiation and progression, so that aggressive tumors can be detected early in the disease process and targeted therapeutic interventions can be deployed. While many studies have been devoted to investigate molecular events in tumorigenesis of oral cancer, most efforts are focused on protein coding genes. The knowledge on the role of non-coding genes (e.g., microRNA) in oral cancer is relatively limited. Our recent studies have demonstrated critical contributions of microRNA deregulation in oral cancer. However, the comprehensive microRNA alteration pattern associated with early stage oral cancer is still lacking, which hindered the potential utilization of microRNA as diagnostic biomarkers. Brush oral cytology is a minimally-invasive method that can be used to collect cells from suspect oral lesions for histological and biochemical analyze. Our recent results demonstrated that we can consistently measure RNA markers in the brush oral cytology samples. In this study, we will identify unique microRNA signatures that associated with early stage oral cancer from the brush oral cytology samples (Specific Aim 1). We will then test the diagnostic values of these microRNA markers in an independent sample set (Specific Aim 2). Statistical classification models will be developed to assess the diagnostic values of these microRNAs. This proposal combines minimally-invasive methods with the emerging genomic technologies to harness microRNA determinants in oral cancer. The outcomes from this study will provide strong rationale and scientific foundation for more extensive patient- based studies to identify and validate microRNA biomarkers for early detection of oral cancer.